In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
In this paper, we propose a new image clustering algorithm, referred to as Clustering using Local Discriminant Models and Global Integration (LDMGI). To deal with the data points s...
Yi Yang, Dong Xu, Feiping Nie, Shuicheng Yan, Yuet...
We propose a technique to recognize actions of grasshoppers based on spectral clustering. We track the object in 3D and construct features using 3D object movement in segments of ...
Background: A routine goal in the analysis of microarray data is to identify genes with expression levels that correlate with known classes of experiments. In a growing number of ...